Sales organizations go through the CRM selection process with great diligence. They spend even more resources redesigning existing processes, integrating the technology and people, training and rolling out the shiny new thing with great fanfare. Making sure every sales person is empowered.
Yet adoption remains at an abysmal level by measures beyond logins, “clicking on plays” and “call blocks.” Why?
Here are three most cited reasons aggregated from numerous research:
It is delivered primarily as a technical tool, relegating the human element.
It is perceived as management pushing something from above.
It is not believed to generate more value: sales, profits, targets.
In other words, it is not adding value to the life of the sales person.
One sales leader I know used to say, “if you don’t know the value of what you’re doing, then stop doing it. You will find out.” Yes, we are asking you to consider the opposite of what every expert says, everything you have heard, and even what we’ve said on these pages – stop doing SFA – if you are not sure of the value being delivered.
But wait, you say! How could we stop using SFA? Well, you start by MAKING IT SCARCE.
If you really believe you are adding value with your SFA, then start by giving it to less people. Select a team, or select reps via a lottery system. If not the entire SFA, then some components which are considered valuable should only go to a select few. Make it a privilege to get these components.
No pushing from the top management tier. If a few sales reps using the system see that their lives are better, they meet goals easier, it is intuitive to use, that data is accurate, analytics is meaningful and timely, and it flows well with their daily activities, then acceptance and adoption of the system will spread throughout the sales force.
Make the SFA about adding value, the people who are using it, and the results being delivered. And forget about adoption rates.
It’s no secret that sales force automation (SFA) was dreaded not too long back, but has now become an indispensable friend to the sales person. There are many who may still be leery of it, but that number is certainly dwindling. Lauren Carlson’s blog at Software Advice reflects on this sales force automation evolution over the past 15 years, and identifies four factors that explain the change. While we agree with those, here’s our take on where this is headed.
The central theme as we see it (of course being a SaaS company ourselves) is 1) the deployment of SFA on SaaS platforms and 2) SFA is more inter-operable in a sales environment. And that is a great fit to how the best sales people think and act: sales is seen in the larger context of client and business needs. So while software engineering has taken great leaps forward with usability, content and inter-operability, it has made it easier rather than harder for sales reps to use these tools.
Let us now envision what the future holds in terms of increasing adoption and further making SFA an indispensable tool for the reps of today and tomorrow.
SIMPLIFY, SIMPLIFY, SIMPLIFY:
Thanks to Amazon, Google, Apple and iPhones, and other innovators, we now live in a world where our tools and devices instantly empower us with just a touch of a finger. There is no need to over-engineer features and functionality. So we will see SFA applications mimic more closely the way sales reps live and work, intuitively pulling things together for the right communication with customers that build credibility and trust.
BETTER INTEGRATION OF ANALYTICS AND DECISION SUPPORT:
Either through native interface, APIs or other methods, information will become more context-sensitive. In other words not “all the data all the time” – that’s like using a cannon to kill a mosquito! Predictive analytics is not used just to determine which customers to contact and what to sell etc., it will also determine when a particular insight or data point is valuable and present it to the sales rep at the right time. The integration of up-to-date sales intelligence tools is further validation of this trend.
GREATER RELIANCE ON SALES PROCESSES THAT PRODUCE RESULTS:
A proven process is a collection of technology, domain knowledge and best practices that are known to produce a better result. There is enough body of knowledge to show what practices work where and why. Sales organizations are already building on this. In addition, the availability of domain expertise and the relative ease of technology integration further drive the dependence on an established process. No SFA = no process.
With the advent of smart phones, tablets and social media we are now at a tipping point with respect to the next evolution of SFAs. It’s no longer a question of should sales team use sales force automation. Companies and sales organizations that do not embrace it and follow a solid process are at a disadvantage. That only portends more exciting times ahead for those that do.
Our CRM trends to watch in 2011 were among the most-read words here, all year. Now let’s look forward to what’s in store for sales and marketing data in 2012 …
FUSION OF SFA WITH EMA = TRUE CRM:
With continuing innovation, sales force automation systems (SFA) have been transformed into a sales rep’s best friend, as discussed in an insightful blog post at Software Advice: easier implementation, data accessibility and now the benefits of analytics and marketing automation are aiding the success of sales teams using these systems.
The success of CRM and Marketing Automation is no secret. More B2B organizations will take advantage of this profitable alliance to create a true lead generation life cycle platform, so that the handoffs throughout the prospect -> lead -> nurture -> sale pipeline will become more seamless and accountable. To accomplish this, data, analytics and best practices will play an integral part in relevant communication.
The customer value equation will go further so companies and sales teams can generate more revenue and profit from existing customers. This means examining every aspect of customer value, determining where it will come from and coaching/training to empower sales teams with the appropriate tools to realize such value.
CUSTOMER OWNERSHIP:
With relationships becoming increasingly more mobile and social (and perhaps personal too), there will be contention on who actually owns the customer: is it the rep, the company or the data/app provider? We’ve already seen lawsuits on such components like blog subscriber lists, Facebook and Twitter connections etc. This is going to become more blurred with the continued growth of social media. One way companies can keep the upper hand is to establish a fair and transparent process.
EXTERNAL INTEGRATION OF CUSTOMER DATA:
Companies have been bringing data together for many years internally, but they only know about what customers do with them. Now via external providers like Facebook or aggregators, there is going to be great interest in knowing about a customer holistically, not just the two-way relationship that companies already know. Privacy considerations included, these will start becoming available on the market.
BIG DATA:
Data trends we discussed last year continue to play out, but one megawave arching over all is Big Data. At the moment, this trend feels more like a solution looking for a problem at the company level. Although age-old techniques like statistical sampling are more cost-efficient, with the need to analyze data across, within, and outside companies and the larger market, more valuable applications will come to market and help realize the benefit of a Big Data strategy.
The excitement of implementing a tool that solves basic operational problems is understandable. The front-end responsibility of reliability, inter-operability and security is clearly with IT. These challenges are significant.
But it is important to go beyond the technology’s bells and whistles. By establishing a vision for analytics – metrics, measurement methods, forward-looking indicators and performance management – and incorporating these in the design, the rationale for the CRM system and its ROI can be validated. Through predictive analytics, business processes can be mapped and modeled, and benchmarks created for delivering quantifiable goals to the enterprise via the CRM system.
For example, is the primary objective of your CRM to support lead generation, product penetration or customer retention? Based on your needs, predictive analytics can help develop appropriate forward-looking indicators, expected results and diagnostics of the results at all levels of activity – customer, sales people, products and operational areas. This will allow ongoing correction and calibration of your activity within the CRM system that maintains the focus on the business outcomes, not just at preset review times or at the end of the year.
Implement analytics-based decision processes
Because initial concerns of getting the CRM system up and running usually consumes all priorities, many organizations do not plan enough for life after implementation. There are three specific areas where predictive analytics can help drive ongoing adoption and value of the investment. Design these components at implementation:
Data integration: To produce valuable predictive analytics, a significant volume of data regardless of source must be brought together, cleansed and summarized. Design the system to provide succinct information at the rep’s fingertips, so they get big-picture visibility about customer trends.
Action recommendations: Translate insights into specific steps within a decisioning process. This should start with the sales rep at the center, looking at the customer portfolio holistically. Set an amount of time to spend on each customer based on expected return for each customer interaction. These actions should be part of a deliberate, systematic, established process flow that sales and business leaders know will be acceptable to the users.
Performance feedback: Integral to the decisioning process is showing sales reps (the users) the results and consequences of their actions. No sales person likes leaving money on the table, we think. Feedback should show relative performance of the reps against a control group (also called “business as usual”), peer group and team. These results should be delivered timely – latent enough to be meaningful and short enough to correct developing trends.
Predictive analytics can add significant value when you are considering, selecting and deploying CRM systems. Including your analytic needs up-front rather than as an afterthought can ensure that the CRM system supports your business objectives and outcomes. While the importance of technical requirements are the backbone of a great implementation, making business analytics a close partner can pay rich dividends.
When presenting our solutions to address issues like new customer growth or optimizing relationships, clients often ask, “but isn’t that what our CRM is supposed to do?” Yes, it can, but the intelligence to empower the CRM system can be driven by predictive analytics.
Customer Relationship Management (CRM) systems are the currency of customer-sales interactions. Effective, simple CRM software helps sales reps to focus on content of conversations rather than the mechanics of conversations, resulting in sales empowerment and productivity gains.
A CRM system can be a boon to sales people. CRM helps overcome the technology hurdle of accessing information over disparate systems. CRM systems help improve collaboration within, above and across the entire organization, allowing the company to speak with one voice. And from a governance perspective, these systems help elevate the customer relationship from individual dependencies to an enterprise-wide strategic asset.
When you add the potency of predictive analytics, a CRM system can be even more valuable. Leaders in analytics, sales operations and technology can fulfill their obligation towards sales empowerment by creating a cohesive approach that brings these disciplines together.
How well we achieve this determines if a CRM system just gains basic acceptance, or whether it is fully adopted and even embraced by sales people who realize its benefits for themselves as well as for their customers.
Here are guidelines to help make that happen:
Consider a multi-stage deployment
In the first stage of CRM implementation, deliver base functionality to the users so that their immediate, tactical pain points are addressed. This often involves getting the system up and running and available without interruption – the kind of stuff that builds rapport with the sales team. It can include consolidating contact hierarchy and transaction history, integrating with hardware (i.e., computer, phones) and software (procurement, shipping), and even interacting with social media.
In subsequent deployment stages, add features – often not present in out-of-the-box CRM systems – that build credibility with sales, extend the functionality and improve the outcomes of customer interaction. This is where predictive analytics can lead the charge. In order to identify hidden opportunities and capitalize on customer interactions, predictive analytics requires three components:
Synthesizing extensive amounts of data, including cleansing and reduction base on insights
Applying data mining and robust statistical methods
Integrating relevant and distilled intelligence back into CRM
These stages need not run in sequence. You can the basic team in place while initiating the gathering of data relevant for analytics. Then insights gained from analytics can help you prioritize implementation decisions.
Tomorrow, more guidelines to help you get the most out of your CRM system with predictive analytics …
